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Added fable/feast support #2045

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35 changes: 35 additions & 0 deletions R/layers2traces.R
Original file line number Diff line number Diff line change
Expand Up @@ -613,6 +613,41 @@ to_basic.GeomQuantile <- function(data, prestats_data, layout, params, p, ...){
dat
}

to_basic.GeomHiloLinerange <- function(data, ...){
prefix_class(data, "GeomPath")
}

transform_hiloribbon <- function(data) {
data <- data[order(data$x), ]
data$hilo <- NULL

data$x_plotlyDomain <- as.character(data$x_plotlyDomain)

maximum_lev <- max(data$level) + 1

data$alpha <- (maximum_lev * (maximum_lev - data$level) - 1 )/ maximum_lev**3
data$colour <- data$alpha

unused_aes <- ! names(data) %in% c("x", "y", "ymin", "ymax")

row_number <- nrow(data)

data_rev <- data[row_number:1L, ]
structure(rbind(
cbind(x = data$x, y = data$ymin, data[unused_aes]),
cbind(x = data$x[row_number], y = data$ymin[row_number], data[row_number, unused_aes]),
cbind(x = data_rev$x, y = data_rev$ymax, data_rev[unused_aes])
), class = class(data))
}
Comment on lines +620 to +641
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Come to think of it, I think most of this as well as to_basic.GeomAlluvium() could be replaced by ribbon_dat()?

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It's the same code with minor changes.


to_basic.GeomHiloRibbon <- function(data, ...){
prefix_class(transform_hiloribbon(data), "GeomPolygon")
}

#' @export
to_basic.data.frame <- function(data, prestats_data, layout, params, p, ...) {
prefix_class(data, "GeomPath")
}
Comment on lines +648 to +650
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Hmm, this doesn't seem right, do you have an example where this becomes relevant?

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this is actually a trick because the autoplot returns only a data.frame and GeomHilo... this results in only drawing the predictions without the line.

#' @export
to_basic.default <- function(data, prestats_data, layout, params, p, ...) {
data
Expand Down
1 change: 1 addition & 0 deletions tests/testthat/_snaps/fabletools/autoplot-fable.svg
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15 changes: 15 additions & 0 deletions tests/testthat/test-fabletools.R
Original file line number Diff line number Diff line change
@@ -0,0 +1,15 @@
test_that("mimics the autoplot output", {
# taken from https://fable.tidyverts.org/articles/fable.html
data <- tsibble::tourism %>%
filter(Region == "Melbourne") %>%
`[`(, c("Quarter", "Trips", "Region")) %>%
distinct(Quarter, .keep_all = TRUE) %>%
as_tsibble(key = Region)
p <- data %>%
model(
ets = ETS(Trips ~ trend("A")),
) %>%
forecast(h = "5 years") %>%
autoplot(data)
expect_doppelganger(ggplotly(p), "autoplot-fable")
})